the basis for Ascent predictive models

Exceptional returns of Ascent portfolios have been achieved by utilizing rigorous quantitative mathematical models and algorithms for money management, risk reduction, and market prediction. These models and algorithms are based on a novel mathematical technique called Neural Modelling Fields (NMF). Preliminary development of this technology was performed with the Department of Defence sponsorship at Nichols Research Corporation (a premier US defense contractor) for recognition and prediction of military targets and signals. The book describing this technology and many of its applications is about to be published by Oxford University Press ("Neural Networks and Intellect: using model-based concept", L.I. Perlovsky, September, 2000).

A conceptual undestanding of NMF and its applicability to the financial markets can be illustrated by comparing it to G. Soros’ reflexivity theory. The reflexivity theory is a psychological theory of interaction between investors and financial markets. It formed a foundation for G. Soros’s management of his extremely successful Quantum fund. The three main concepts of the theory of reflexivity are: (1) the fundamentally-imperfect character of our knowledge, (2) the two-way dynamic relationships between the knowledge and the outer world (reflexivity), and (3) multiple processes operating concurrently. Mr. Soros correctly suggested that existing mathematical methods were inadequate for describing his type of theory. Solutions for every one of the above three features required a fundamentally new mathematical-statistical concept. The solutions where obtained by Dr. Perlovsky; they overcame the deficiencies of the previous neural network, pattern recognition, and artificial intelligence techniques and they formed the foundation of NMF. The close correspondence between NMF and reflexivity theory is due to the fact that both theories describe the dynamics of human minds in their interaction with the world, in this case, the financial markets.